Put it into action

Let’s get to the part where the magic happens. You already know we’re in behavior modeling mode now. Below, we’ll help you get the most out of reward loops in the design, experimentation, and feedback phases.

Reward Loop Decision Tree →

  • Go to "File" → "Make a Copy"
  • If you’re having initiation, completion, or retention problems, you can use the decision tree to see what’s wrong and how to fix it
  • We’ll give in-depth feedback on your experiments or loop ideas on this week’s Zoom call; make sure to put these ideas into action and share your work


Work & Personal Experiment Design

‍Launching an experiment takes time. When that doesn’t work, at least we can organize our data, brainstorm experiments, make predictions, and learn how to troubleshoot different challenges when they come up. This mental work is as important as running a test and analyzing the data.

Questions to ask when designing loops for others:

  1. Who has gotten this population or audience to do this behaviour or reach this outcome successfully? What were the loops and components? What seems to work?
  2. Who has successfully gotten this demographic to do similar behaviours or kept them engaged with something for a long time? What pains did they remove, and what rewards did the experience provide?
  3. What experiences does this group of people seek out for purely hedonic reasons, where do they spend their discretionary time, and what do they find rewarding?
  4. What parts of the loop seem to be the highest-leverage areas to play with? What experiments do we predict might be most effective?

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Designing Behaviour for Yourself
The best behavioural scientists we know are often experimenting in their own lives, where they can get data much faster and shorten feedback cycles.

You can do quick-and-dirty experiments with reward loops in your own life around personal goals you might have. Even if the behaviour or tactics aren't relevant to others, practicing this kind of thinking and design can translate to your professional work.

Example: How can I experiment with designing the first and subsequent iterations of reward loops for myself to do X more often or consistently?

  • Think of an activity you want to start doing (or doing more often). How can you make the it more enjoyable, easy, and motivating? Pick an experiment and see if it works.
  • To reduce screen time, list the antecedents that increase the chances of you reducing time on your phone/laptop. Change the antecedents or triggers in your environment (e.g., where and what you’re doing in the evenings) and track your screen time.
  • Consider a behaviour you stopped doing. Figure out if (or why) it was more punishing than rewarding, what antecedents undermined the behavior, or what other factors caused the loop to fail. Outline the parts of the loop and try to identify where the highest-impact fix might be. Then consider the recurring cycles of the reward loop, and figure out what changes after a week, a month, and so on.


Zoom, Loom, and Slack

  • If there are any questions you have about this week’s lesson, ask them on Slack and or have them ready for Thursday’s Zoom call
  • You can also drop us requests for feedback on any document, design, or personal/work experiment that relates to behavior change, and we'll do our best to respond with a short video. Feel free to send a Loom link yourself (~5 min or less).
  • You can request feedback that’s public or private, but we’ll prioritize public so more people can learn from each others’ work.


That's it for week 3. Let's go design some loops and experiments!